| What do neural machine translation models learn about morphology? Y Belinkov, N Durrani, F Dalvi, H Sajjad, J Glass Proceedings of the 55th Annual Meeting of the Association for Computational …, 2017 | 475 | 2017 |
| Robust classification of crisis-related data on social networks using convolutional neural networks D Nguyen, KA Al Mannai, S Joty, H Sajjad, M Imran, P Mitra Proceedings of the international AAAI conference on web and social media 11 …, 2017 | 272 | 2017 |
| Compressing large-scale transformer-based models: A case study on bert P Ganesh, Y Chen, X Lou, MA Khan, Y Yang, H Sajjad, P Nakov, D Chen, ... Transactions of the Association for Computational Linguistics 9, 1061-1080, 2021 | 223 | 2021 |
| Identifying and Controlling Important Neurons in Neural Machine Translation A Bau, Y Belinkov, H Sajjad, N Durrani, F Dalvi, J Glass ICLR, 2019 | 211 | 2019 |
| What is one grain of sand in the desert? analyzing individual neurons in deep nlp models F Dalvi, N Durrani, H Sajjad, Y Belinkov, A Bau, J Glass Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 6309-6317, 2019 | 209 | 2019 |
| Fighting the COVID-19 infodemic: Modeling the perspective of journalists, fact-checkers, social media platforms, policy makers, and the society F Alam, S Shaar, F Dalvi, H Sajjad, A Nikolov, H Mubarak, GDS Martino, ... arXiv preprint arXiv:2005.00033, 2020 | 186 | 2020 |
| The AMARA Corpus: Building Parallel Language Resources for the Educational Domain. A Abdelali, F Guzman, H Sajjad, S Vogel LREC 14, 1044-1054, 2014 | 148 | 2014 |
| On the effect of dropping layers of pre-trained transformer models H Sajjad, F Dalvi, N Durrani, P Nakov Computer Speech & Language 77, 101429, 2023 | 143 | 2023 |
| Fighting the COVID-19 infodemic in social media: A holistic perspective and a call to arms F Alam, F Dalvi, S Shaar, N Durrani, H Mubarak, A Nikolov, ... Proceedings of the International AAAI Conference on Web and Social Media 15 …, 2021 | 140 | 2021 |
| Evaluating layers of representation in neural machine translation on part-of-speech and semantic tagging tasks Y Belinkov, L Màrquez, H Sajjad, N Durrani, F Dalvi, J Glass arXiv preprint arXiv:1801.07772, 2018 | 135 | 2018 |
| Applications of online deep learning for crisis response using social media information DT Nguyen, S Joty, M Imran, H Sajjad, P Mitra arXiv preprint arXiv:1610.01030, 2016 | 127 | 2016 |
| Poor man’s bert: Smaller and faster transformer models H Sajjad, F Dalvi, N Durrani, P Nakov arXiv preprint arXiv:2004.03844 2 (2), 2020 | 115 | 2020 |
| Integrating an Unsupervised Transliteration Model into Statistical Machine Translation N Durrani, H Sajjad, H Hoang, P Koehn EACL 2014, 148, 2014 | 113 | 2014 |
| Incremental decoding and training methods for simultaneous translation in neural machine translation F Dalvi, N Durrani, H Sajjad, S Vogel arXiv preprint arXiv:1806.03661, 2018 | 109 | 2018 |
| Analyzing redundancy in pretrained transformer models F Dalvi, H Sajjad, N Durrani, Y Belinkov arXiv preprint arXiv:2004.04010, 2020 | 105 | 2020 |
| Analyzing individual neurons in pre-trained language models N Durrani, H Sajjad, F Dalvi, Y Belinkov arXiv preprint arXiv:2010.02695, 2020 | 104 | 2020 |
| CrisisBench: Benchmarking crisis-related social media datasets for humanitarian information processing F Alam, H Sajjad, M Imran, F Ofli Proceedings of the International AAAI conference on web and social media 15 …, 2021 | 96 | 2021 |
| Similarity analysis of contextual word representation models JM Wu, Y Belinkov, H Sajjad, N Durrani, F Dalvi, J Glass arXiv preprint arXiv:2005.01172, 2020 | 85 | 2020 |
| Neuron-level interpretation of deep nlp models: A survey H Sajjad, N Durrani, F Dalvi Transactions of the Association for Computational Linguistics 10, 1285-1303, 2022 | 83 | 2022 |
| On the linguistic representational power of neural machine translation models Y Belinkov, N Durrani, F Dalvi, H Sajjad, J Glass Computational Linguistics 46 (1), 1-52, 2020 | 83 | 2020 |
Nadir DurraniSenior Scientist, QCRI, HBKUhbku.edu.qa의 이메일 확인됨